Modelling the World of a Smart Room for Robotic Co-working

Conference paper
Part of the Communications in Computer and Information Science book series (CCIS, volume 880)


Robots come out of the cage. Soon, it will be possible to interact with free-standing robots along an assembly line or in a manufacturing workshop (robotic co-working). New sensitive robot arms have appeared on the market [1] that slow down or stop when humans enter their context, which creates rich opportunities for collaboration between human and robots. But how to program them? This paper contributes an architectural design pattern to engineer software for robotic co-working with world-oriented modelling (WOM). We argue that robotic co-working always has to take place in smart rooms tracking the movements of humans carefully, so that the robotic system can automatically adapt to their actions. Because robotic co-working should be safe for humans, robots, and their work items, the robots should enter safe states before harmful encounters happen. Based on the safety automata in the style of [1], we suggest to engineer software for the smart rooms of human-robotic co-working with an explicit world model, an automaton of the world’s states, and a software variant space, a software variant family, which are related by a total activation mapping. This construction has the advantage that the world model is split off the software system to make its construction simpler, avoiding if-bloated code. Also, proofs about the entire smart system can be split into a proof about the world model and a proof obligation for the software variant space. Therefore, we claim that world-oriented modelling (WOM) simplifies the development of robotic co-working applications, leveraging the principle of separation of concerns for improved maintainability and quality assurance.


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© Springer International Publishing AG, part of Springer Nature 2018

Authors and Affiliations

  1. 1.Chair of Software Engineering, Fakultät InformatikTechnische Universität DresdenDresdenGermany

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